Artificial Intelligence and Advanced Analytics in Healthcare

  • ID: 4425690
  • Report
  • 43 Pages
  • Frost & Sullivan
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Sustainable Sourcing of Innovations from Emerging Markets is Critical for Sustainable Long-term Profitable Growth of Global Product Portfolios

The global healthcare industry is in need of solutions that augment providers with insights to make meaningful clinical decisions within less turnaround times, which is critical to demonstrating value of care. Artificial Intelligence has proven its utility in performing data-mining activities on large sets of patient and population health data, addressing vital gaps in automating the clinical workflow. Adoption of artificial intelligence technologies has reduced healthcare costs by 50%, while improving patient outcome by over 50%. Advanced analytic frameworks evaluate 'unstructured data', such as physician-entered notes, health statistics, clinical literature and radiology reports to deliver trends critical to improving the quality of healthcare.

This research service (RS) offers a strategic perspective on the impact of artificial intelligence (AI) and advanced analytics on the global healthcare industry. This RS has been segmented into five chapters, with the first two focusing on analysis of the top trends from both technology and competitive perspectives. the third, fourth and fifth chapters focus on the global adoption landscape, reviewing the roles and strategies of both existing and emerging participants.

Key Questions Answered by this Eesearch Services (RS):

  1. What are the major classes of artificial intelligence and advanced analytics technologies? What are the sub-classification of technologies for various clinical applications by commercial attractiveness and intensity of patenting activities?
  2. Who are the key stakeholders within the global healthcare industry, including medical device companies, pharmaceutical companies and biotechnology firms that are pioneering technology development initiatives for driving sustainable market growth efforts across potential markets?
  3. What is the role of stakeholders across the value chain and their efforts towards development of technologies?
  4. How has the global competitive landscape evolved over the past decade, especially with respect to those innovating artificial intelligence solutions for addressing needs faced by the global healthcare industry?
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1. Executive Summary
1.1 Scope of Research
1.2 Research Methodology
1.3 AI Has Proved Its Utility in Performing Complex Data Mining Activity and Assisting Physicians Make Better Treatment Decisions
1.4 Diagnostic Centers Have Been Early Adopters and Late Majority in Terms of Their Level of Adoption of AI-based Solutions
1.5 Better High Adoption of Speech Recognition Techniques Comes With Achieving Interoperability of Electronic Health Records

2. Technology Overview
2.1 Very High Adoption of Speech Recognition Techniques Comes With Achieving Interoperability of Electronic Health Records (EHRs)
2.2 Advanced Technologies Such as Predictive Modelling Holds Very High Potential to Reduce Turnaround Time During Drug Discovery Process
2.3 High Market Adoption of Artificial Intelligence Tools Comes With Their Ability to Support Complex Clinical Decisions in Lesser Time
2.4 Artificial intelligence is a Critical Tool For Healthcare Companies to Differentiate Their Existing Products Across Potential Markets

3. Global Competitive Scenario
3.1 Academic Research and Non-healthcare Companies Surpass Traditional Healthcare Companies in the Adoption of Artificial Intelligence Solutions
3.2 Predictive modelling Offers More Scope For Diversification of Existing Product Lines Across Newer and Unexplored Areas
3.3 Solutions Created Using Machine Learning and Cognitive Computing Deliver Scope For Sustainable Market Growth Worldwide

4. Global Adoption Landscape
4.1 Most Artificial Intelligence Solutions Are Yet to Demonstrate Their Clinical Value in the Field of Surgery
4.2 Deep Learning as an AI-based Technique Has Been Widely Examined Worldwide as a Solution to Support Clinical Decision Making
4.3 Natural Language Processing Provides Better Clinical Value Across Customer Segments With High Commercialization Potential

5. Global Technology Value Chain
5.1 Healthcare IT Firms Play a Vital Role Within the Innovation Ecosystem, Being Early Adopters of Technologies Addressing Needs on Time
5.2 Healthcare Providers, Biotech Firms and Pharma Companies Deliver Very High Synergies For Growth Across the Value Chain
5.3 Solutions to Optimize Patient Data, and Improving Decision Making Are Among the Top Growth Agendas of Global Innovation Stakeholders
5.4 Medtronic, Roche, and GE Healthcare Are Among the Top Adopters of AI-based Technologies to Develop Better Clinical Solutions

6. Strategic Recommendations
6.1 Technology Developers Need to Source Innovations From Emerging Markets to Fuel Cutting-edge Global New Product Development Efforts
6.2 Developing a Periodic Technology Tracking Program is Critical For Identifying Disruptive Solutions That Complement Existing Solutions
6.3 Case in Point: Developing Deep Learning Algorithms For Detecting Skin Cancer Malignancies
6.4 Case in Point: Addressing Adverse Events and Quality Control Processes Using Pharmacovigilance Artificial Intelligence Solutions
6.5 The Pace of Technology Adoption is Critical For Developing Innovative Solutions Addressing Customer Needs

7. Patent Landscape Assessment
7.1 North American and European Countries Hold High Intensity of Patents, Dominating the Global Patent Landscape
7.2 Development of a System For Approximating a Deep Neural Network For Anatomical Object Detection
7.3 Deep Learning Offers Advantage in Identifying Potential Risks in Reporting the Risk to Healthcare Providers
7.4 Development of Mobile Applications For Reliable Communication of Patient’s Medical Information Across Healthcare Facilities
7.5 Key Contacts
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  • GE Healthcare
  • Medtronic
  • Roche
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